AI ML Engineering Visa Sponsorship Jobs in North Carolina
North Carolina's AI/ML engineering job market is anchored by Research Triangle Park, one of the largest research and technology corridors in the country, with employers like Red Hat, Cisco, Lenovo, and SAS Institute actively hiring. Duke University and NC State also feed strong graduate pipelines into the region's growing AI infrastructure and data science sectors.
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Get Access To All JobsINTRODUCTION
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Raleigh, NC, USA; Durham, NC, USA.
MINIMUM QUALIFICATIONS:
- Bachelor’s degree, or equivalent practical experience.
- 8 years of experience in software development.
- 3 years of experience with developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage or hardware architecture.
- 3 years of experience in a technical leadership role.
- 2 years of experience in a people management or team leadership role.
- Experience developing software applications using the C++ programming language.
PREFERRED QUALIFICATIONS:
- Master's degree or PhD in Computer Science or a related technical field.
- 3 years of experience working in a complex, matrixed organization.
- Experience with Nvidia Collective Communications Library (NCCL), Nvidia Index Library (NIXL), Deep Learning Execution Provider (DeepEP), and Mooncake.
ABOUT THE JOB
Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of Engineers. You not only optimize your own code but make sure Engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started - and as a manager, you guide the way.
With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally.
Network Infrastructure Team's mission is to be an expert in the hardware-software interface, and to influence the co-design of Google software and hardware to strike the right balance between performance-optimized hardware and the implications of the API design on software performance and maintainability.
In this role, you will work with hardware designers, vendors, and Google software teams alike, you will think about the software and hardware performance, and how API design affects these. You will work on specific offload technologies, including AI Training and Inference Transport Layers as well as dataplane encryption. The ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world.
We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Cloud’s Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.
The US base salary range for this full-time position is $207,000-$300,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.
Responsibilities
- Set and communicate team priorities that support the broader organization's goals.
- Manage and lead the team that is developing the next generation Artificial Intelligence (AI) and Machine Learning (ML) Networking solutions as well as Smart Network Interface Cards (NICs) at Google, taking the projects through development into production.
- Enable the team to advance new approaches to leverage offloads efficiently with Google hardware and software.
- Guide the team to build and test software in C++ for use on Google's Machine Learning (ML) Library solutions and Smart Network Interface Cards (NICs).
- Align strategy, processes, and decision-making across teams.
Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.
INTRODUCTION
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Raleigh, NC, USA; Durham, NC, USA.
MINIMUM QUALIFICATIONS:
- Bachelor’s degree, or equivalent practical experience.
- 8 years of experience in software development.
- 3 years of experience with developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage or hardware architecture.
- 3 years of experience in a technical leadership role.
- 2 years of experience in a people management or team leadership role.
- Experience developing software applications using the C++ programming language.
PREFERRED QUALIFICATIONS:
- Master's degree or PhD in Computer Science or a related technical field.
- 3 years of experience working in a complex, matrixed organization.
- Experience with Nvidia Collective Communications Library (NCCL), Nvidia Index Library (NIXL), Deep Learning Execution Provider (DeepEP), and Mooncake.
ABOUT THE JOB
Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of Engineers. You not only optimize your own code but make sure Engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started - and as a manager, you guide the way.
With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally.
Network Infrastructure Team's mission is to be an expert in the hardware-software interface, and to influence the co-design of Google software and hardware to strike the right balance between performance-optimized hardware and the implications of the API design on software performance and maintainability.
In this role, you will work with hardware designers, vendors, and Google software teams alike, you will think about the software and hardware performance, and how API design affects these. You will work on specific offload technologies, including AI Training and Inference Transport Layers as well as dataplane encryption. The ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world.
We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Cloud’s Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.
The US base salary range for this full-time position is $207,000-$300,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.
Responsibilities
- Set and communicate team priorities that support the broader organization's goals.
- Manage and lead the team that is developing the next generation Artificial Intelligence (AI) and Machine Learning (ML) Networking solutions as well as Smart Network Interface Cards (NICs) at Google, taking the projects through development into production.
- Enable the team to advance new approaches to leverage offloads efficiently with Google hardware and software.
- Guide the team to build and test software in C++ for use on Google's Machine Learning (ML) Library solutions and Smart Network Interface Cards (NICs).
- Align strategy, processes, and decision-making across teams.
Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.
AI ML Engineering Job Roles in North Carolina
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Search AI ML Engineering Jobs in North CarolinaAI ML Engineering Jobs in North Carolina: Frequently Asked Questions
Which companies sponsor visas for AI/ML engineers in North Carolina?
Several large technology and research employers in North Carolina have established H-1B sponsorship track records, including SAS Institute, Red Hat, Cisco, Lenovo, and IBM, which maintain significant operations in the Research Triangle area. Healthcare technology companies such as Labcorp and Syneos Health also sponsor AI/ML roles. Checking DOL Labor Condition Application disclosure data shows which employers have filed LCAs for machine learning and AI engineering positions specifically.
Which visa types are most common for AI/ML engineering roles in North Carolina?
The H-1B is the most common visa for AI/ML engineers in North Carolina, as these roles typically qualify as specialty occupations requiring at least a bachelor's degree in computer science, data science, or a related field. The O-1A is an option for engineers with documented extraordinary ability, such as published research or patents. F-1 graduates from NC State, Duke, or UNC can work on OPT or STEM OPT before an employer files an H-1B petition.
How to find ai ml engineering visa sponsorship jobs in North Carolina?
Migrate Mate filters AI/ML engineering jobs specifically by visa sponsorship availability, making it straightforward to identify North Carolina employers actively open to sponsoring international candidates. Rather than manually screening hundreds of listings, you can search Migrate Mate for roles in cities like Raleigh, Durham, Charlotte, and Cary, where most of the state's AI hiring is concentrated.
Which cities in North Carolina have the most AI/ML engineering sponsorship jobs?
Raleigh and Durham are by far the most active cities for AI/ML engineering sponsorship, driven by Research Triangle Park and the proximity to NC State University and Duke University. Charlotte has a growing technology sector with AI roles tied to financial services and fintech companies. Cary, which hosts SAS Institute's headquarters, is another consistent source of machine learning and data engineering positions open to sponsored candidates.
Are there state-specific factors AI/ML engineers should know when pursuing sponsorship in North Carolina?
Research Triangle Park's concentration of technology, life sciences, and enterprise software companies means AI/ML roles here often overlap with biomedical data and clinical analytics, which can affect the degree field an employer lists on the LCA. NC State's well-regarded computer science and statistics programs create a large local candidate pool, so demonstrating specialized ML expertise, graduate-level education, or relevant research experience tends to strengthen sponsorship petitions filed by North Carolina employers.
What is the prevailing wage for sponsored ai ml engineering jobs in North Carolina?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.
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